Package: PoolTestR 0.2.1

PoolTestR: Prevalence and Regression for Pool-Tested (Group-Tested) Data

An easy-to-use tool for working with presence/absence tests on 'pooled' or 'grouped' samples. The primary application is for estimating prevalence of a marker in a population based on the results of tests on pooled specimens. This sampling method is often employed in surveillance of rare conditions in humans or animals (e.g. molecular xenomonitoring). The package was initially conceived as an R-based alternative to the molecular xenomonitoring software, 'PoolScreen' <https://sites.uab.edu/statgenetics/software/>. However, it goes further, allowing for estimates of prevalence to be adjusted for hierarchical sampling frames, and perform flexible mixed-effect regression analyses (McLure et al. Environmental Modelling and Software. <doi:10.1016/j.envsoft.2021.105158>). The package is currently in early stages, however more features are planned or in the works: e.g. adjustments for imperfect test specificity/sensitivity, functions for helping with optimal experimental design, and functions for spatial modelling.

Authors:Angus McLure [aut, cre], Caitlin Cherryh [ctb]

PoolTestR_0.2.1.tar.gz
PoolTestR_0.2.1.zip(r-4.7-x86_64)PoolTestR_0.2.1.zip(r-4.7-arm64)PoolTestR_0.2.1.zip(r-4.6-x86_64)PoolTestR_0.2.1.zip(r-4.6-arm64)PoolTestR_0.2.1.zip(r-4.5-x86_64)
PoolTestR_0.2.1.tgz(r-4.6-x86_64)PoolTestR_0.2.1.tgz(r-4.6-arm64)PoolTestR_0.2.1.tgz(r-4.5-x86_64)PoolTestR_0.2.1.tgz(r-4.5-arm64)
PoolTestR_0.2.1.tar.gz(r-4.7-arm64)PoolTestR_0.2.1.tar.gz(r-4.7-x86_64)PoolTestR_0.2.1.tar.gz(r-4.6-arm64)PoolTestR_0.2.1.tar.gz(r-4.6-x86_64)
PoolTestR_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PoolTestR/json (API)

# Install 'PoolTestR' in R:
install.packages('PoolTestR', repos = c('https://angusmclure.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/angusmclure/pooltestr/issues

Uses libs:
  • onetbb– Parallelism library for C++
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

onetbbcpp

4.02 score 7 stars 8 scripts 350 downloads 1 mentions 8 exports 89 dependencies

Last updated from:8de4f3e5dc. Checks:13 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE319
linux-devel-x86_64NOTE355
source / vignettesOK369
linux-release-arm64NOTE314
linux-release-x86_64NOTE284
macos-release-arm64NOTE321
macos-release-x86_64NOTE564
macos-oldrel-arm64NOTE345
macos-oldrel-x86_64NOTE588
windows-devel-arm64NOTE537
windows-devel-x86_64NOTE463
windows-release-arm64NOTE538
windows-release-x86_64NOTE406
windows-oldrel-x86_64NOTE404
wasm-releaseOK204

Exports:CheckInputDatagetPrevalenceHierPoolPrevPoolLinkPoolPrevPoolRegPoolRegBayesPrepareClusterData

Dependencies:abindbackportsbayesplotBHbootbridgesamplingbrmsBrobdingnagcallrcheckmateclicodacodetoolscpp11crayondescdigestdistributionaldplyrfarverfuturefuture.applygenericsggdistggplot2ggridgesglobalsgluegridExtragtablehmsinlineisobandlabelinglatticelifecyclelistenvlme4loomagrittrMASSMatrixmatrixStatsmgcvminqamvtnormnleqslvnlmenloptrnumDerivotelparallellypillarpkgbuildpkgconfigplyrposteriorprettyunitsprocessxprogresspspurrrquadprogQuickJSRR6rbibutilsRColorBrewerRcppRcppEigenRcppParallelRdpackreformulasreshape2rlangrstanrstantoolsS7scalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr